Against the background of the digitalization of care, service-dominant logic can be used scientifically as a structuring framework in health care research. In Germany, the basics of service-dominant logic, whose applicability to care has been discussed internationally for around 10 years, are closely linked to the basics and considerations of the so-called performance theory, which was largely developed in the 1990s by Werner Hans Engelhardt, Michael Kleinaltenkamp and other researchers (Benkenstein 2008). Even after this, a clear separation of services and benefits in kind is not possible. Rather, combined service bundles are the subject of transactions between parties involved. This also applies to medical-clinical treatments, regardless of whether they have a preventative, curative or palliative intention. The extensive focus on the use of products, whether in diagnostics or therapy, and the isolated consideration of their effects is by no means sufficient, especially for health services research. Product-focused innovations are changing care configuration and coordination. Knowledge about product application becomes part of medical-clinical knowledge, but the associated transformation effects are not measured in detail. As is well known, the level of detail is not sufficient to unequivocally and comprehensively explain the effectiveness under care conditions (e.g. stage/disease progression, age, multimorbidity, genetic predispositions). The supply process is too complex, too variable and ultimately too non-transparent in terms of data. The SDL can make a contribution to the structured investigation of care phenomena that have not yet been transparent to the necessary level of detail.

>> Service-Dominant Logic (SDL) is a theory that was not developed for health services research. Rather, it was initially developed for marketing in the sense of a scientific discipline and out of the realization that classic exchange models in economics are not sufficient to scientifically describe the phenomena associated with exchange in the sense of a scientific understanding of marketing. According to Lusch and Vargo (Vargo and Lusch 2004), the main reason was that the focus of Goods-Dominant Logic (GDL) was on manufactured goods, products, i.e. tangible resources, to which one could easily assign a value. On the other hand, less attention has been paid to intangible resources and associated phenomena, for example the “co-creation” of services in the sense of resource integration and relationship phenomena with regard to exchange processes. The parallels between the genesis of SDL and health care research, which in its early days examined more intensively the doctor-patient relationship and its effects on treatment outcomes, are unmistakable. The above-mentioned and by no means complete phenomena are also highly relevant for health services research, especially since they are only becoming scientifically accessible in depth, breadth and timely thanks to the technical possibilities of digitalization. This also applies to the investigation of “co-creation” phenomena in health services research. The joint interaction between service providers and patients for the purpose of optimal treatment results through targeted resource integration is increasingly being conveyed via digital applications. This is essential for understanding but also for evaluating the processes and instruments used for care. The heterogeneity inherent in care, which is also caused by patients (e.g. gender, age, multimorbidity) and care settings, can initially be recorded descriptively using SDL approaches and, after interpretation, can be better understood normatively, for example to define optimization corridors for selected care topics (petition Steeghs et al. 2020).
The study of “co-creation” as a result of a primarily digitally mediated exchange between service providers and patients has far-reaching consequences. As a result, there is a paradigm shift that gives patients a more active role through patient engagement in healthcare research settings (Harrington et al. 2020). In the research setting, your role is increasingly one of an active partnership or leadership role that makes patient-centeredness possible. This research paradigm shift contributes to a better understanding of the care process from the patient's perspective. This allows possible care goals and the fulfillment of care needs to be optimized taking patient preferences into account. The growing relevance of intangible resources is due to increasingly complex exchange processes that are technology and innovation-driven. This also applies to medical care. The focus that is relevant for patients is often lost (Joiner and Lusch 2016). The preferences are less abstract: survival, living longer, living better, seeing better. The path to get there is largely irrelevant for patients, although complex approaches have to be used: the risk-adjusted care of people with BRCA mutation proven by molecular diagnostics (current focus: women), precision oncological therapies that are initiated on the basis of molecular pathological differential diagnosis, and the treatment of autoimmune diseases such as multiple sclerosis with digital health applications or the emerging cell and gene therapy approaches, which require complex care approaches such as intensive care follow-up treatment in order to be able to be used successfully. This also applies analogously to other areas of technology. While in the past automobiles were sold with a definable and simple performance profile (acceleration, braking, etc.), the software components of a car are increasingly crucial for differentiation. On the one hand, they ensure optimal mobility performance and, on the other hand, the usage data generated and shared by users allows continuous improvement of future service offerings. This situation can also be transferred to medical care. Of course, hemodialysis does not just consist of connecting the patient to a blood purification machine with a known filtration profile. Diagnostic information about the patient's clinical condition is crucial in order to iteratively exploit the full potential of a complex dialysis machine for the benefit of the patient based on this information. Here too, the comprehensive evaluation of the data improves renal replacement therapy in incremental steps. This also includes information on the perception of the treatment and life situation, represented by recording instruments: preference measurements, recording instruments for quality of life as well as PROMs (patient-reported outcome measures) and PREMs (patient-reported experience measures). In these contexts, it is ultimately about building up and using knowledge and skills (intangible, “operant resources”) in the sense of the SDL in such a way that the use of medical technology, medicines including diagnostics, etc. (tangible, “operand resources”) in combination With human attention and targeted communication, a service is created that is ultimately optimized and can also be measured as a patient-relevant additional benefit. The results can then be interpreted and evaluated in a scientifically comparative manner using additional perspectives, such as quality, patient safety, HTA or “value-based health care”.
The way in which tangible and intangible resources are integrated within the framework of a service that can also be defined clinically (e.g. ophthalmologist: cataract treatment, patient: “being able to see clearly again”) can be analyzed from multiple perspectives (see Fig. 1): is the service Given the current state of medicine, is it efficient, is it effective, does it meet the patient's disease-specific preferences? The terms used in the SDL are not intended to address health or care-specific issues. Rather, the SDL terms need to be applied to the respective research questions from the perspective of health services research.
The term service is of great scientific importance in SDL; one does not speak of “services” (Vargo and Akaka 2009). In abstract terms, service is an act or action in which something is done for a person, either directly or through the use of products. The “service” for the treatment of a cataract (cataract) today usually consists of diagnostics, the use of an extracapsular surgical technique with phacoemulsification including the provision of an intraocular lens, followed by a short follow-up including medication. Success and the risk of complications depend less on the products used (including intraocular lenses), but rather on the individual treatment process components actually carried out and their sequence. The service is therefore easily accessible with regard to care as a complete or partial process. And it is precisely this that needs to be scientifically examined in more detail in order to ultimately be able to derive the optimal care. Optimal care must also be interpreted in the context of medical progress. When implemented, the digitalization of health services research can help to classify a service (e.g. cataract treatment, dialysis) in accordance with the SDL.
It is understood that no final classification of the treatment result is possible, but that in this logic one can retrieve the current state of scientific knowledge with the help of data slices. The data-driven feedback with patients being treated helps to capture a benefit that is relevant to them, which can also include not using products or not always using them.

Use and benefits for health services research
The SDL theory building has a benefit for health services research. SDL can be used as a metastructure. The approach can generate contributions to a better understanding of care. The perspectives of health services research are expanded. Qualitative, empirical, clinical-epidemiological or health economic approaches can be methodically integrated into the metastructure. In healthcare, the aim is to better understand the use of evidence-based effective products (e.g. diagnostics, drugs, medical devices for invasive interventions, including AI-supported diagnosis and treatment algorithms) in variable, heterogeneous settings. A holistically viewed care setting can be modeled in the SDL as an ecosystem in which complex exchange processes take place between different actors, e.g. service providers and patients. The supply ecosystems are established through resource integration of tangible and intangible components via “co-creation” (Frow et al. 2016).

Challenges in applying the SDL
The SDL is not fully adapted to health services research issues. The approaches require scientific operationalization. They must be adapted to the respective question from the perspective of health services research. The questions can then be addressed using well-known and established methods from health sciences, psychology, health economics and statistics. <<

Prof. Dr. Dr. Klaus Nagels, Faculty of Law and Economics /
Chair of Medical Management and Health Services Research at the University of Bayreuth
“Service-Dominant Logic is a theoretical approach that can be applied to health care research in an interdisciplinary manner. It expands the structured analysis tools of patient-centered care. It represents a link between analog and digital supply. It allows complex relationships to be researched. The investigation of 'co-creation' phenomena that serve a holistic resource integration is only
mentioned as an example. This allows patients’ direct or indirect contributions and the associated effects of the transformation towards optimized care to be better understood.”